John Callegari
Founder at Stealth Startup
Seattle, Washington, United States
Summary
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Top SchoolJohn Callegari is a founder and lead data scientist with eight years of industry experience building medical AI that drives clinical decision support and funds growth—he played a pivotal role in securing $23M in Series A financing at ImpriMed. Trained in biophysics and computer science at Yale and Johns Hopkins, he brings deep domain expertise in cancer biology, genomics, and translational research with a track record of peer-reviewed publications and FDA-facing analytics. He has built and deployed a dozen ML models in production for oncology, engineered data pipelines from massive EHR and NGS sources, and developed specialized TensorFlow modules to handle missing labels and per-patient inferencing. Equally at home in research and production, he reduced ML research costs by 90% in prior roles and open-sourced a Ray-based library for distributed ML pipelines used for large-scale algorithmic experiments. Based in Seattle, he’s now founding a stealth medical AI startup aiming to automate the scientific method to improve human health.
7 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Cellular and Molecular Medicine, Doctor of Philosophy (Ph.D.) Cellular and Molecular Medicine at The Johns Hopkins University School of MedicineBS Molecular Biophysics and Biochemistry, BS Molecular Biophysics and Biochemistry at Yale University
English, French
Github Skills (44)
data-analysis10
python10
data-science10
statistics10
machine-learning10
scikit9
scikit-learn9
scriptable9
compose8
jetpack7
notebook7
knowledge-management7
kotlin7
trilium6
xamarin-forms6
Programming languages (6)
Github contributions (5)
ajcallegari/scikit-multichannel
Jun 2020 - Dec 2022
Python library for multichannel machine learning and semi-auto-ML.
Contributions:3 releases, 246 commits, 233 pushes in 2 years 5 months
python-librarypythonmultichanneldata-sciencesemi
ajcallegari/aws-elastic-beanstalk-express-js-sample
Apr 2024 - Apr 2024
Sample web application for the AWS DevOps Engineer Learning Path.
Contributions:1 push in 1 day
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